@inproceedings{harshita-etal-2023-verb,
title = "Verb Categorisation for {H}indi Word Problem Solving",
author = "Sharma, Harshita and
Mishra, Pruthwik and
M. Sharma, Dipti",
editor = "D. Pawar, Jyoti and
Lalitha Devi, Sobha",
booktitle = "Proceedings of the 20th International Conference on Natural Language Processing (ICON)",
month = dec,
year = "2023",
address = "Goa University, Goa, India",
publisher = "NLP Association of India (NLPAI)",
url = "https://aclanthology.org/2023.icon-1.59/",
pages = "613--628",
abstract = "Word problem Solving is a challenging NLP task that deals with solving mathematical probglems described in natural language. Recently, there has been renewed interest in developing word problem solvers for Indian languages. As part of this paper, we have built a Hindi arithmetic word problem solver which makes use of verbs. Additionally, we have created verb categorization data for Hindi. Verbs are very important for solving word problems with addition/subtraction operations as they help us identify the set of operations required to solve the word problems. We propose a rule-based solver that uses verb categorisation to identify operations in a word problem and generate answers for it. To perform verb categorisation, we explore several approaches and present a comparative study."
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="harshita-etal-2023-verb">
<titleInfo>
<title>Verb Categorisation for Hindi Word Problem Solving</title>
</titleInfo>
<name type="personal">
<namePart type="given">Harshita</namePart>
<namePart type="family">Sharma</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Pruthwik</namePart>
<namePart type="family">Mishra</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Dipti</namePart>
<namePart type="family">M. Sharma</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2023-12</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 20th International Conference on Natural Language Processing (ICON)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Jyoti</namePart>
<namePart type="family">D. Pawar</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Sobha</namePart>
<namePart type="family">Lalitha Devi</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>NLP Association of India (NLPAI)</publisher>
<place>
<placeTerm type="text">Goa University, Goa, India</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>Word problem Solving is a challenging NLP task that deals with solving mathematical probglems described in natural language. Recently, there has been renewed interest in developing word problem solvers for Indian languages. As part of this paper, we have built a Hindi arithmetic word problem solver which makes use of verbs. Additionally, we have created verb categorization data for Hindi. Verbs are very important for solving word problems with addition/subtraction operations as they help us identify the set of operations required to solve the word problems. We propose a rule-based solver that uses verb categorisation to identify operations in a word problem and generate answers for it. To perform verb categorisation, we explore several approaches and present a comparative study.</abstract>
<identifier type="citekey">harshita-etal-2023-verb</identifier>
<location>
<url>https://aclanthology.org/2023.icon-1.59/</url>
</location>
<part>
<date>2023-12</date>
<extent unit="page">
<start>613</start>
<end>628</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Verb Categorisation for Hindi Word Problem Solving
%A Sharma, Harshita
%A Mishra, Pruthwik
%A M. Sharma, Dipti
%Y D. Pawar, Jyoti
%Y Lalitha Devi, Sobha
%S Proceedings of the 20th International Conference on Natural Language Processing (ICON)
%D 2023
%8 December
%I NLP Association of India (NLPAI)
%C Goa University, Goa, India
%F harshita-etal-2023-verb
%X Word problem Solving is a challenging NLP task that deals with solving mathematical probglems described in natural language. Recently, there has been renewed interest in developing word problem solvers for Indian languages. As part of this paper, we have built a Hindi arithmetic word problem solver which makes use of verbs. Additionally, we have created verb categorization data for Hindi. Verbs are very important for solving word problems with addition/subtraction operations as they help us identify the set of operations required to solve the word problems. We propose a rule-based solver that uses verb categorisation to identify operations in a word problem and generate answers for it. To perform verb categorisation, we explore several approaches and present a comparative study.
%U https://aclanthology.org/2023.icon-1.59/
%P 613-628
Markdown (Informal)
[Verb Categorisation for Hindi Word Problem Solving](https://aclanthology.org/2023.icon-1.59/) (Sharma et al., ICON 2023)
ACL
- Harshita Sharma, Pruthwik Mishra, and Dipti M. Sharma. 2023. Verb Categorisation for Hindi Word Problem Solving. In Proceedings of the 20th International Conference on Natural Language Processing (ICON), pages 613–628, Goa University, Goa, India. NLP Association of India (NLPAI).